Michael Mastro

U.S. Naval Research Laboratory

  • Exploring the capability of Hyperspectral Electroluminescence for process monitoring in vertical GaN devices

    Karl D. Hobart, U.S. Naval Research Laboratory
    Mona Ebrish, Vanderbilt University, Nashville, TN
    Travis J. Anderson, U.S. Naval Research Laboratory
    James Gallagher, U.S. Naval Research Laboratory
    Joseph Spencer, U.S. Naval Research Laboratory
    Jennifer Hite, U.S. Naval Research Laboratory
    Michael Mastro, U.S. Naval Research Laboratory

    GaN is a promising material for more efficient high frequency and high voltage power switching. However, GaN still is not the common material for power electronics due to immature substrate, homoepitaxial growth, and processing technology. Electroluminescence is a promising method to predict failure points due to high field stress, which can assist in the separation of inherent defects stemming from substrate quality, and from process-induced defects as well as identify problems related to proper edge termination design. In this work, we compare the Electroluminescence signatures of devices on inhomogeneous substrates to DC I-V behavior to demonstrate the utility of the technique for process monitoring.

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  • 10.5.2023 Accuracy of Machine Learning Models on Predicting the Properties of Vertical GaN Diodes

    James Gallagher, U.S. Naval Research Laboratory
    Michael A. Mastro, U.S. Naval Research Laboratory
    Mona Ebrish, Vanderbilt University, Nashville, TN
    Alan Jacobs, U.S. Naval Research Laboratory
    Brendan. P. Gunning, Sandia National Labs, Albuquerque, NM
    Robert Kaplar, Sandia National Labs, Albuquerque, NM

    10.5.2023_Gallagher